code: def fit(self, X):
      train = self._series_to_supervised(
          X, n_in=self.n_past, n_out=self.n_future
      )
      trainX, trainy = (
          train[:, : -self.n_future],
          train[:, -self.n_future :],
      )
      self.model = self.model.fit(trainX, trainy)
      return self
  
file_path: AIX360/tests/tssaliency/test_tssaliency.py
imports: import os
  import unittest
  import numpy
  import pandas
  from sklearn.model_selection import train_test_split
  from sklearn.ensemble import RandomForestRegressor
  from aix360.algorithms.tsutils.tsframe import tsFrame
  from aix360.datasets import SunspotDataset
  from aix360.algorithms.tssaliency import TSSaliencyExplainer
label_desc: Use image node_id 2 for calling the RandomForestUniVariateForecaster obj's underlying member method code with example usage: obj.fit(X) and returns: self